Thijs Baan
Applied Psychologist & Lead Engineer @Info Support
Ede, The Netherlands
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Thijs is an Applied Psychologist and Lead Engineer at Info Support. With a background in software engineering and psychology, he helps teams navigate complex technical challenges while understanding the human side of change and innovation. Pragmatic and structured in his approach, he is driven by a curiosity for the interaction between people and technology.
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Are We Getting Hooked on AI Dopamine?
Agentic AI gives us something we never had before: instant feedback on every decision, every prompt, every output. Direct suggestions. A constant stream of next steps. That's efficient. That's productive. But what does that steady flow of reward do to our attention and behavior? Are we quietly becoming addicted to AI dopamine?
This lightning talk examines agentic engineering through the lens of dopamine, reward, and habit formation. When feedback is immediate and output quality keeps varying, a hard-to-ignore pattern emerges: prompt, evaluate, retry, one more time. That's exactly what makes this way of working not just powerful, but behaviorally addictive at the micro level.
The session breaks down how that reward loop operates in everyday engineering work. Why does "one more prompt" feel so logical? And why is stopping often harder than you'd expect? You'll walk away with a clearer picture of why you fall into this loop, how to recognize it in your own AI use, and what you can do to step out of it without losing the benefits AI brings.
Trusting AI: What It Reveals About Us
As engineers, we know AI is built on algorithms and probabilities. But in practice, the hardest part is often not the system itself. It is how we as people respond to it. The problem is not just that AI makes mistakes, but that we react strongly to both its mistakes and its confidence.
We already trust AI with a lot. We use copilots to move faster, generate ideas, and reduce routine work. But while we rely on these systems every day, we often react differently to their mistakes than we do to human mistakes. We accept mistakes from colleagues because we understand that humans are imperfect. With AI, one wrong answer can make us dismiss it too quickly, while a confident answer can make us rely on it too easily.
This talk explores trust in AI through the lens of psychology. It argues that trust in AI is not a simple matter of trust or distrust, but a calibration problem. Through examples from coding and AI-assisted workflows, you will learn why people misjudge AI and how overtrust and undertrust show up in engineering work. You will leave with a clearer sense of when to rely on AI, when to verify it, and how to stay in control without losing its benefits.
Cognitive Shift: How Agentic AI Changes the Way We Think
Copilots and agentic AI are not only changing how we work as software engineers, but also how we think. In this session, we look beyond productivity claims and tool comparisons, and focus on the psychological side of AI Augmented Engineering. What happens to your attention, working memory, critical thinking, and mental models when AI starts to take over more of the writing, searching, and thinking?
In this talk, we explore why working with AI often feels faster and smoother, while at the same time creating new kinds of mental friction. As AI increasingly provides output, suggestions, and next steps, the role of the engineer shifts: from building things yourself to evaluating, choosing, checking, and steering. This directly affects focus, understanding, learning, debugging, and keeping track of context. Using recognizable real-world situations, we look at where AI creates mental space, where it adds cognitive load, and what this means for how engineers develop expertise.
This session gives you a practical psychological framework to use AI more consciously and effectively in your daily work. You’ll learn how to recognize when AI improves speed, focus, and mental space, when it quietly adds extra cognitive load, and how to deal with that in a smart way. This helps you get more out of copilots and agents, without losing sharpness, understanding, and control, as AI becomes an increasingly essential part of engineering.
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